Deep Proteomic Compound Profiling with the Orbitrap Ascend Tribrid Mass Spectrometer Using Tandem Mass Tags and Real-Time Search.

Tandem mass tags (TMT) and tribrid mass spectrometers are a powerful combination for high-throughput proteomics with high quantitative accuracy. Increasingly, this technology is being used to map the effects of drugs on the proteome. However, the depth of proteomic profiling is still limited by sensitivity and speed. The new Orbitrap Ascend mass spectrometer was designed to address these limitations with a combination of hardware and software improvements. We evaluated the performance of the Ascend in multiple contexts including deep proteomic profiling. We found that the Ascend exhibited increased sensitivity, yielding higher signal-to-noise ratios than the Orbitrap Eclipse with shorter injection times. As a result, higher numbers of peptides and proteins were identified and quantified, especially with low sample input. TMT measurements had significantly improved signal-to-noise ratios, improving quantitative precision. In a fractionated 16plex sample that profiled proteomic differences across four human cell lines, the Ascend was able to quantify hundreds more proteins than the Eclipse, many of them low-abundant proteins, and the Ascend was able to quantify >8000 proteins in 30% less instrument time. We used the Ascend to analyze 8881 proteins in HCT116 cancer cells treated with covalent sulfolane/sulfolene inhibitors of peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1), a phosphorylation-specific peptidyl-prolyl cis-trans isomerase implicated in several cancers. We characterized these PIN1 inhibitors' effects on the proteome and identified discrepancies among the different compounds, which will facilitate a better understanding of the structure-activity relationship of this class of compounds. The Ascend was able to quantify statistically significant, potentially therapeutically relevant changes in proteins that the Eclipse could not detect.

Dynamic Data-Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment.

Data-independent acquisition (DIA) mass spectrometry has grown in popularity in recent years, because of the reproducibility and quantitative rigor of a systematic tandem mass spectrometry (MS/MS) sampling method. However, traditional DIA methods may spend valuable instrument time acquiring MS/MS spectra with no usable information in them, affecting sensitivity and quantitative performance. We developed a DIA strategy that dynamically adjusts the MS/MS windows during the chromatographic separation. The method focuses MS/MS acquisition on the most relevant mass range at each point in time─increasing the quantitative sensitivity by increasing the time spent on each DIA window. We demonstrate an improved lower limit of quantification, on average, without sacrificing the number of peptides detected.

Real-Time Spectral Library Matching for Sample Multiplexed Quantitative Proteomics.

Sample multiplexed quantitative proteomics assays have proved to be a highly versatile means to assay molecular phenotypes. Yet, stochastic precursor selection and precursor coisolation can dramatically reduce the efficiency of data acquisition and quantitative accuracy. To address this, intelligent data acquisition (IDA) strategies have recently been developed to improve instrument efficiency and quantitative accuracy for both discovery and targeted methods. Toward this end, we sought to develop and implement a new real-time spectral library searching (RTLS) workflow that could enable intelligent scan triggering and peak selection within milliseconds of scan acquisition. To ensure ease of use and general applicability, we built an application to read in diverse spectral libraries and file types from both empirical and predicted spectral libraries. We demonstrate that RTLS methods enable improved quantitation of multiplexed samples, particularly with consideration for quantitation from chimeric fragment spectra. We used RTLS to profile proteome responses to small molecule perturbations and were able to quantify up to 15% more significantly regulated proteins in half the gradient time compared to traditional methods. Taken together, the development of RTLS expands the IDA toolbox to improve instrument efficiency and quantitative accuracy for sample multiplexed analyses.

Improved Structural Characterization of Glycerophospholipids and Sphingomyelins with Real-Time Library Searching.

In mass spectrometry-based lipidomics, complex lipid mixtures undergo chromatographic separation, are ionized, and are detected using tandem MS (MSn) to simultaneously quantify and structurally characterize eluting species. The reported structural granularity of these identified lipids is strongly reliant on the analytical techniques leveraged in a study. For example, lipid identifications from traditional collisionally activated data-dependent acquisition experiments are often reported at either species level or molecular species level. Structural resolution of reported lipid identifications is routinely enhanced by integrating both positive and negative mode analyses, requiring two separate runs or polarity switching during a single analysis. MS3+ can further elucidate lipid structure, but the lengthened MS duty cycle can negatively impact analysis depth. Recently, functionality has been introduced on several Orbitrap Tribrid mass spectrometry platforms to identify eluting molecular species on-the-fly. These real-time identifications can be leveraged to trigger downstream MSn to improve structural characterization with lessened impacts on analysis depth. Here, we describe a novel lipidomics real-time library search (RTLS) approach, which utilizes the lipid class of real-time identifications to trigger class-targeted MSn and to improve the structural characterization of phosphotidylcholines, phosphotidylethanolamines, phosphotidylinositols, phosphotidylglycerols, phosphotidylserine, and sphingomyelins in the positive ion mode. Our class-based RTLS method demonstrates improved selectivity compared to the current methodology of triggering MSn in the presence of characteristic ions or neutral losses.

Benchmarking the Orbitrap Tribrid Eclipse for Next Generation Multiplexed Proteomics.

The rise of sample multiplexing in quantitative proteomics for the dissection of complex phenotypic comparisons has been advanced by the development of ever more sensitive and robust instrumentation. Here, we evaluated the utility of the Orbitrap Eclipse Tribrid mass spectrometer (advanced quadrupole filter, optimized FTMS scan overhead) and new instrument control software features (Precursor Fit filtering, TurboTMT and Real-time Peptide Search filtering). Multidimensional comparisons of these novel features increased total peptide identifications by 20% for SPS-MS3 methods and 14% for HRMS2 methods. Importantly Real-time Peptide Search filtering enabled a ∼2× throughput improvement for quantification. Across the board, these sensitivity increases were attained without sacrificing quantitative accuracy. New hardware and software features enable more efficient characterization in pursuit of comparative whole proteome insights.

Comparison of data acquisition strategies on quadrupole ion trap instrumentation for shotgun proteomics.

The most common data collection in shotgun proteomics is via data-dependent acquisition (DDA), a process driven by an automated instrument control routine that directs MS/MS acquisition from the highest abundant signals to the lowest. An alternative to DDA is data-independent acquisition (DIA), a process in which a specified range in m/z is fragmented without regard to prioritization of a precursor ion or its relative abundance in the mass spectrum, thus potentially offering a more comprehensive analysis of peptides than DDA. In this work, we evaluate both DDA and DIA on three different linear ion trap instruments: an LTQ, an LTQ modified with an electrodynamic ion funnel, and an LTQ Velos. These instruments represent both older (LTQ) and newer (LTQ Velos) ion trap designs (i.e., linear versus dual ion traps, respectively), and allow direct comparison of peptide identifications using both DDA and DIA analysis. Further, as the LTQ Velos has an enhanced "S-lens" ion guide to improve ion flux, we found it logical to determine if the former LTQ model could be leveraged by improving sensitivity by modifying with an electrodynamic ion guide of significantly different design to the S-lens. We find that the ion funnel enabled LTQ identifies more proteins in the insoluble fraction of a yeast lysate than the other two instruments in DIA mode, whereas the faster scanning LTQ Velos performs better in DDA mode. We explore reasons for these results, including differences in scan speed, source ion optics, and linear ion trap design.

Novel parallelized quadrupole/linear ion trap/Orbitrap tribrid mass spectrometer improving proteome coverage and peptide identification rates.

Proteome coverage and peptide identification rates have historically advanced in line with improvements to the detection limits and acquisition rate of the mass spectrometer. For a linear ion trap/Orbitrap hybrid, the acquisition rate has been limited primarily by the duration of the ion accumulation and analysis steps. It is shown here that the spectral acquisition rate can be significantly improved through extensive parallelization of the acquisition process using a novel mass spectrometer incorporating quadrupole, Orbitrap, and linear trap analyzers. Further, these improvements to the acquisition rate continue to enhance proteome coverage and general experimental throughput.

Multiplexed MS/MS for improved data-independent acquisition.

In mass spectrometry-based proteomics, data-independent acquisition (DIA) strategies can acquire a single data set useful for both identification and quantification of detectable peptides in a complex mixture. However, DIA data are noisy owing to a typical five- to tenfold reduction in precursor selectivity compared to data obtained with data-dependent acquisition or selected reaction monitoring. We demonstrate a multiplexing strategy, MSX, for DIA analysis that increases precursor selectivity fivefold.

Evaluation of front-end higher energy collision-induced dissociation on a benchtop dual-pressure linear ion trap mass spectrometer for shotgun proteomics.

We report the implementation of front-end higher energy collision-induced dissociation (fHCD) on a benchtop dual-pressure linear ion trap. Software and hardware modifications were employed, described in detail vide-infra, to allow isolated ions to undergo collisions with ambient gas molecules in an intermediate multipole (q00) of the instrument. Results comparing the performance of fHCD and resonance excitation collision-induced dissociation (RE-CID) in terms of injection time, total number of scans, efficiency, mass measurement accuracy (MMA), unique peptide identifications, and spectral quality of labile modified peptides are presented. fHCD is approximately 23% as efficient as RE-CID, and depending on the search algorithm, it identifies 6.6% more or 15% less peptides (q < 0.01) from a soluble whole-cell lysate ( Caenorhabditis elegans ) than RE-CID using Mascot or Sequest search algorithms, respectively. fHCD offers a clear advantage for the analysis of phosphorylated and glycosylated (O-GlcNAc) peptides as the average cross-correlation score (XCorr) for spectra using fHCD was statistically greater (p < 0.05) than for spectra collected using RE-CID.

A high voltage asymmetric waveform generator for FAIMS.

High field asymmetric waveform ion mobility spectrometry (FAIMS) has been used increasingly in recent years as an additional method of ion separation and selection before mass spectrometry. The FAIMS electrodes are relatively simple to design and fabricate for laboratories wishing to implement their own FAIMS designs. However, construction of the electronics apparatus needed to produce the required high magnitude asymmetric electric field oscillating at a frequency of several hundred kilohertz is not trivial. Here we present an entirely custom-built electronics setup capable of supplying the required waveforms and voltages. The apparatus is relatively simple and inexpensive to implement. We also present data acquired on this system demonstrating the use of FAIMS as a gas-phase ion filter interface to an ion trap mass spectrometer.

Assessing the dynamic range and peak capacity of nanoflow LC-FAIMS-MS on an ion trap mass spectrometer for proteomics.

Proteomics experiments on complex mixtures have benefited greatly from the advent of fast-scanning ion trap mass spectrometers. However, the complexity and dynamic range of mixtures analyzed using shotgun proteomics is still beyond what can be sampled by data-dependent acquisition. Furthermore, the total liquid chromatography-mass spectrometry (LC-MS) peak capacity is not sufficient to resolve the precursors within these mixtures, let alone acquire tandem mass spectra on all of them. Here we describe the application of a high-field asymmetric waveform ion mobility spectrometry (FAIMS) device as an interface to an ion trap mass spectrometer. The dynamic range and peak capacity of the nanoflow LC-FAIMS-MS analysis was assessed using a complex tryptic digest of S. cerevisiae proteins. By adding this relatively simple device to the front of the mass spectrometer, we obtain an increase in peak capacity >8-fold and an increase in dynamic range of >5-fold, without increasing the length of the LC-MS analysis. Thus, the addition of FAIMS to the front of a table-top mass spectrometer can obtain the peak capacity of multidimensional protein identification technology (MudPIT) while increasing the throughput by a factor of 12.

Label-free comparative analysis of proteomics mixtures using chromatographic alignment of high-resolution muLC-MS data.

Label-free relative quantitative proteomics is a powerful tool for the survey of protein level changes between two biological samples. We have developed and applied an algorithm using chromatographic alignment of microLC-MS runs to improve the detection of differences between complex protein mixtures. We demonstrate the performance of our software by finding differences in E. coli protein abundance upon induction of the lac operon genes using isopropyl beta-D-thiogalactopyranoside. The use of our alignment gave a 4-fold decrease in mean relative retention time error and a 6-fold increase in the number of statistically significant differences between samples. Using a conservative threshold, we have identified 5290 total microLC-MS regions that have a different abundance between these samples. Of the detected difference regions, only 23% were mapped to MS/MS peptide identifications. We detected 74 proteins that had a greater relative abundance in the induced sample and 21 with a greater abundance in the uninduced sample. We have developed an effective tool for the label-free detection of differences between samples and demonstrate an increased sensitivity following chromatographic alignment.

Semi-supervised learning for peptide identification from shotgun proteomics datasets.

Shotgun proteomics uses liquid chromatography-tandem mass spectrometry to identify proteins in complex biological samples. We describe an algorithm, called Percolator, for improving the rate of confident peptide identifications from a collection of tandem mass spectra. Percolator uses semi-supervised machine learning to discriminate between correct and decoy spectrum identifications, correctly assigning peptides to 17% more spectra from a tryptic Saccharomyces cerevisiae dataset, and up to 77% more spectra from non-tryptic digests, relative to a fully supervised approach.